Overview of Dempster-Shafer and Belief Function Tracking Methods

Over the years, there have been many proposed methods in set-based tracking. One example of set-based methods is the use of Dempster-Shafer (DS) techniques to support belief-function (BF) tracking. In this paper, we overview the issues and concepts that motivated DS methods for simultaneous tracking and classification/identification. DS methods have some attributes, if applied correctly; but there are some pitfalls that need to be carefully avoided such as the redistribution of the mass associated with conflicting measurements. Such comparisons and applications are found in Dezert-Smarandache Theory (DSmT) methods from which the Proportional Conflict Redistribution (PCR5) rule supports a more comprehensive
approach towards applying evidential and BF techniques to target tracking. In the paper, we overview two decades of research in the area of BF tracking and conclude with a comparative analysis of Bayesian, Dempster-Shafer, and the PCR5 methods.